全局模糊c均值(GFCM)聚类算法在色彩传递中的应用

Xinhua Zou, Ruomei Wang, Zhong Wang, Yong-ping Liu
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引用次数: 1

摘要

提出了一种基于全局模糊c均值(GFCM)聚类算法的色彩传递方法。采用GFCM算法在l - αβ空间中定位图像之间的匹配区域,防止聚类处理陷入局部最优解。实验表明,与传统的FCM方法相比;GFCM方法可以在更短的时间内获得更好的聚类结果,获得更自然、更流畅的视觉效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Application of Global Fuzzy C-Means (GFCM) Clustering Algorithm in Color Transfer
This paper proposes a color transfer approach based on Global Fuzzy C-Means (GFCM) clustering algorithm. GFCM algorithm is adopted to locate the matching areas between the images in lαβ space and to prevent the clustering processing from falling into the local optimal solution. The experiment shows that comparing to the traditional FCM method; GFCM method can obtain a better clustering result in a shorter time and achieve more natural and smoother visual effects.
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